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首页> 外文期刊>Experiments in Fluids: Experimental Methods and Their Applications to Fluid Flow >Advances in iterative multigrid PIV image processing
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Advances in iterative multigrid PIV image processing

机译：迭代多网格PIV图像处理的进展

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An image-processing technique is proposed, which performs iterative interrogation of particle image velocimetry (PIV) recordings. The method is based on cross-correlation, enhancing the matching performances by means of a relative transformation between the interrogation areas. On the basis of an iterative prediction of the tracers motion, window offset and deformation are applied, accounting for the local deformation of the fluid continuum. In addition, progressive grid refinement is applied in order to maximise the spatial resolution. The performances of the method are analysed and compared with the conventional cross correlation with and without the effect of a window discrete offset. The assessment of performance through synthetic PIV images shows that a remarkable improvement can be obtained ill terms of precision and dynamic range. Moreover, peak-locking, effects do not affect the method in practice. The velocity gradient range accessed with the application of a relative window deformation (linear approximation) is significantly enlarged, as confirmed in the experimental results. [References: 21]
机译：提出了一种图像处理技术，该技术执行粒子图像测速（PIV）记录的迭代查询。该方法基于互相关，通过询问区域之间的相对变换来增强匹配性能。在对示踪剂运动进行迭代预测的基础上，应用窗口偏移和变形，以解决流体连续体的局部变形问题。另外，为了使空间分辨率最大化，应用了渐进的网格细化。分析了该方法的性能，并将其与具有和不具有窗口离散偏移影响的常规互相关进行比较。通过合成的PIV图像对性能进行评估表明，无论在精度还是动态范围方面，都可以获得显着的提高。而且，峰锁效应在实践中不会影响该方法。实验结果证实，通过施加相对窗口变形（线性近似）可达到的速度梯度范围显着扩大。 [参考：21]

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